Abstract
Background
Ankylosing spondylitis (AS) begins early in life and often leads to reduced physical function, but less is known about the impacts it has on health-related quality of life (HRQoL). The aims of this study were to assess HRQoL using the Short Form-36 (SF-36) in a cohort of patients with AS compared with controls and to examine associations between SF-36 scores and spinal radiographic changes, physical function, disease activity and demographic data overall and stratified by sex.
Methods
A cohort of patients with AS from Western Sweden were assessed using the Modified Stoke Ankylosing Spondylitis Spine Score (mSASSS) with spinal radiographs, clinical examination and questionnaires, including the Bath Ankylosing Spondylitis Metrology Index, Bath Ankylosing Spondylitis Functional Index (BASFI), Ankylosing Spondylitis Disease Activity Score-C-reactive protein (ASDAS-CRP), Bath Ankylosing Spondylitis Disease Activity Index, Bath Ankylosing Spondylitis Patient Global (BASG) and SF-36. Each patient’s SF-36 results were compared with those of five age-matched and sex-matched persons (n = 1055) from the SF-36 Swedish normative population database. Associations between SF-36 physical component summary (PCS) and mental component summary (MCS) scores and disease-related and demographic factors were investigated using univariate and multivariable ogistic regression analyses with PCS and MCS below/above their respective median values as dependent variables.
Results
A total of 210 patients, age (median, IQR) 49.0 (21.2) years, symptom duration 24.0 (21.0) years, men 57.6% and HLAB27 87.1% were included. Patients with AS scored significantly lower (p < 0.001) compared to controls in all SF-36 domains and component summaries; PCS 42.4 (14.5) in AS versus 52.4 (11.8) in controls and MCS 47.9 (20.0) in AS versus 54.1 (10.1) in controls. Both men and women scored significantly lower in PCS compared with MCS. Multivariable logistic regression analyses revealed that living without a partner (OR 2.38, 95% CI 1.00–5.67), long symptom duration (year in decade OR 1.66, 95% CI 1.16–2.37), higher BASFI (OR 1.98, 95% CI 1.46–2.70) and ASDAS ≥ 2.1 (OR 3.32, 95% CI 1.45–7.62) were associated with worse PCS, while living without a partner (OR 3.04, 95% CI 1.34–6.91), fatigue (visual analogue scale for global fatigue greater than the median (OR 6.36, 95% CI 3.06–13.19) and ASDAS ≥ 2.1 (OR 2.97, 95% CI 1.41–6.25) with worse MCS. Some differences between sexes were observed in the results.
Conclusions
The patients with AS had significantly lower HRQoL compared with controls. PCS was more affected compared to MCS in both sexes. Both disease-related and demographic factors were associated with HRQoL, partly overlap** for PCS and MCS. Factors associated with HRQoL showed some differences between sexes. By modifying factors, such as ASDAS-CRP and fatigue, HRQoL may potentially be improved.
Trial registration
ClinicalTrials.gov, NCT00858819. Registered on 9 March 2009. Last updated on 28 May 2015.
Similar content being viewed by others
Background
Ankylosing spondylitis (AS) is a chronic inflammatory rheumatic disease primarily affecting the sacroiliac joints and spine [1]. Inflammation of the spinal structures and progressive spinal changes in the vertebrae and surrounding tissue, is largely responsible for the decreased physical function and mobility experienced by patients with AS [2]. Studies of AS often describe functional disabilities and measures of disease activity, however, they less often report the quality of life experienced by patients with AS and how this is related to AS disease characteristics. Health-related quality of life (HRQoL) is a multi-dimensional concept including not only a person’s physical wellbeing, but also a person’s mental health and physical ability, both as an individual and as a participating member of the community. The Medical Outcome Survey Short Form-36 (SF-36) was designed for use in clinical practice and research, health policy evaluations, and general population surveys and is utilised in many different countries [3,4,5,6]. Yang et al. recently performed a meta-analysis based on of 38 studies assessing HRQoL using the SF-36 in patients with AS and found that they had significantly worse HRQoL compared to persons from general populations and that to measure HRQoL should be regarded as an essential part of the overall assessment of patients with AS [35].
The impact on HRQoL of living alone and/or to be unmarried has previously been investigated in other diseases and in the general population, and to the best of our knowledge, for the first time in this study of patients with AS. The literature displays inconsistent results. In patients with chronic diseases such as cancer and multiple sclerosis, living alone is mostly associated with worse HRQoL, which is in line with the findings in our study [36,37,38]. However, in a longitudinal study, decline in the MCS score in patients with diabetes mellitus was associated with not living alone [39]. In a study from China, participants living alone had worse HRQoL [40], while the opposite was reported from another part of China, Shanghai [41]. Women in the Nurses’ Health Study who lived alone had lower risk of decline in the MH and VT domains compared with those living with a spouse. Furthermore, contact with friends and relatives and level of social engagement significantly protected against a decline in MH in women living alone but not among women living with a partner [42]. Thus, the influence of living alone on HRQoL is complex and seems to be related to the persons’ state of health, culture and gender, among other factors.
The sex-stratified analyses in our study revealed some differences; the disease activity seemed to be a more important factor in the physical component of HRQoL in men while the civil state was more important for the mental component of HRQoL in women, which are aspects that can be taken into account in the management of the patients with AS.
There are some limitations to be acknowledged; first this study is cross-sectional and thus we cannot draw any conclusions about the variables identified as associated with worse HRQoL and causality. To investigate this a longitudinal study is required. Second, the SF-36 Swedish normative population database was created in the 1990s and HRQoL in the general population might have changed over the years. However, HRQoL in the general population assessed by the SF-36 was stable from 1996 to 2004 in Norway [43], our neighbouring country, indicating that the difference in time may not be a significant problem. Third, we chose to divide the patients with AS according to their median values of PCS and MCS. Since there is no established cutoff for better or worse HRQoL we used this pragmatic approach. Furthermore, the modest number of subjects in the sex-stratified analyses result in broad confidence intervals and thus results need to be interpreted with some caution. Strengths of this study comprise first, a well-characterised patient cohort with an adequate number of patients allowing subgroup analyses of the sexes to be carried out for the first time. Second, SF-36 scores in patients with AS were compared to those in a large sample of controls from the general population who were precisely matched on sex and age.
Possible implications of our findings include that we have identified variables associated with worse HRQoL, which are modifiable. Even though our study is cross-sectional, and thus not able to show causality, by using these variables as a guide, patients may be treated more efficiently, leading to reduction in disease activity, pain and fatigue, thus potentially improving both the PCS and MCS scores as has been shown in some clinical trials [44,45,46]. To live alone without a partner was also associated with worse HRQoL in particular in women in the MCS score. A focus on social activities and community support for women with AS might help to improve MCS scores in this subset of patients with AS.
Conclusions
In this study we show that the patients with AS had significantly lower HRQoL when assessed by the SF-36, compared with the general population. The PCS score was more affected than the MCS score in both sexes. Both demographic and disease-related factors were associated with worse HRQoL, with partial overlap for the PCS and MCS. There were some differences between sexes in the factors associated with HRQoL. By modifying factors such as ASDAS-CRP and fatigue, HRQoL may potentially be improved. There is a need for longitudinal studies investigating predictors related to the development of HRQoL in AS over time. We intend to investigate factors related to the change in HRQoL over a 5-year period in this same cohort of patients with AS in a future study.
Abbreviations
- AS:
-
Ankylosing spondylitis
- ASAS:
-
Assessment of SpondyloArthritis International Society
- ASDAS:
-
Ankylosing Spondylitis Disease Activity Score
- BASDAI:
-
Bath Ankylosing Spondylitis Disease Activity Index
- BASFI:
-
Bath Ankylosing Spondylitis Functional Index
- BASG:
-
Bath Ankylosing Spondylitis Patient Global
- BASMI:
-
Bath Ankylosing Spondylitis Metrology Index
- BASRI:
-
Bath Ankylosing Spondylitis Radiology Index
- BMI:
-
Body mass index
- BP:
-
Bodily pain
- CI:
-
Confidence interval
- CRP:
-
C-reactive protein
- DMARD:
-
Disease-modifying anti-rheumatic drug
- ESR:
-
Erythrocyte sedimentation rate
- GH:
-
General health
- HLA-B27:
-
Human leukocyte antigen B27
- HRQoL:
-
Health-related quality of life
- IBD:
-
Inflammatory bowel disease
- MCS:
-
Mental component summary
- MH:
-
Mental health
- mSASSS:
-
Modified Stoke Ankylosing Spondylitis Spine Score
- NSAID:
-
Non-steroid anti-inflammatory drug
- OR:
-
Odds ratio
- PCS:
-
Physical component summary
- PF:
-
Physical functioning
- RE:
-
Role emotional
- RP:
-
Role physical
- SD:
-
Standard deviation
- SF:
-
Social functioning
- SF-36:
-
Short form-36
- TNFi:
-
Tumor necrosis factor inhibitor
- VAS:
-
Visual analogue scale
- VT:
-
Vitality
References
Braun J, Sieper J. Ankylosing spondylitis. Lancet. 2007;369(9570):1379–90.
Baraliakos X, Listing J, Rudwaleit M, Haibel H, Brandt J, Sieper J, Braun J. Progression of radiographic damage in patients with ankylosing spondylitis: defining the central role of syndesmophytes. Ann Rheum Dis. 2007;66(7):910–5.
Ware JE Jr, Sherbourne CD. The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care. 1992;30(6):473–83.
Sullivan M, Karlsson J. The Swedish SF-36 Health Survey III. Evaluation of criterion-based validity: results from normative population. J Clin Epidemiol. 1998;51(11):1105–13.
Sullivan M, Karlsson J, Ware JE Jr. The Swedish SF-36 Health Survey–I. Evaluation of data quality, scaling assumptions, reliability and construct validity across general populations in Sweden. Soc Sci Med. 1995;41(10):1349–58.
Persson LO, Karlsson J, Bengtsson C, Steen B, Sullivan M. The Swedish SF-36 Health Survey II. Evaluation of clinical validity: results from population studies of elderly and women in Gothenborg. J Clin Epidemiol. 1998;51(11):1095–103.
Yang X, Fan D, **a Q, Wang M, Zhang X, Li X, Cai G, Wang L, **n L, Xu S, et al. The health-related quality of life of ankylosing spondylitis patients assessed by SF-36: a systematic review and meta-analysis. Qual Life Res. 2016;25(11):2711–23.
Ribu L, Hanestad BR, Moum T, Birkeland K, Rustoen T. A comparison of the health-related quality of life in patients with diabetic foot ulcers, with a diabetes group and a nondiabetes group from the general population. Qual Life Res. 2007;16(2):179–89.
Salaffi F, Carotti M, Gasparini S, Intorcia M, Grassi W. The health-related quality of life in rheumatoid arthritis, ankylosing spondylitis, and psoriatic arthritis: a comparison with a selected sample of healthy people. Health Qual Life Outcomes. 2009;7:25.
Huang JC, Qian BP, Qiu Y, Wang B, Yu Y, Zhu ZZ, Hu J, Qu Z. Quality of life and correlation with clinical and radiographic variables in patients with ankylosing spondylitis: a retrospective case series study. BMC Musculoskelet Disord. 2017;18(1):352.
Vesovic-Potic V, Mustur D, Stanisavljevic D, Ille T, Ille M. Relationship between spinal mobility measures and quality of life in patients with ankylosing spondylitis. Rheumatol Int. 2009;29(8):879–84.
Ozdemir O. Quality of life in patients with ankylosing spondylitis: relationships with spinal mobility, disease activity and functional status. Rheumatol Int. 2011;31(5):605–10.
Machado P, Landewe R, Braun J, Hermann KG, Baraliakos X, Baker D, Hsu B, van der Heijde D. A stratified model for health outcomes in ankylosing spondylitis. Ann Rheum Dis. 2011;70(10):1758–64.
Klingberg E, Carlsten H, Hilme E, Hedberg M, Forsblad-d'Elia H. Calprotectin in ankylosing spondylitis–frequently elevated in feces, but normal in serum. Scand J Gastroenterol. 2012;47(4):435–44. https://doi.org/10.3109/00365521.2011.648953
Lee W, Reveille JD, Davis JC Jr, Learch TJ, Ward MM, Weisman MH. Are there gender differences in severity of ankylosing spondylitis? Results from the PSOAS cohort. Ann Rheum Dis. 2007;66(5):633–8.
Klingberg E, Geijer M, Gothlin J, Mellstrom D, Lorentzon M, Hilme E, Hedberg M, Carlsten H, Forsblad-D'Elia H. Vertebral fractures in ankylosing spondylitis are associated with lower bone mineral density in both central and peripheral skeleton. J Rheumatol. 2012;39(10):1987–95.
van der Linden S, Valkenburg HA, Cats A. Evaluation of diagnostic criteria for ankylosing spondylitis. A proposal for modification of the New York criteria. Arthritis Rheum. 1984;27(4):361–8.
Sieper J, Rudwaleit M, Baraliakos X, Brandt J, Braun J, Burgos-Vargas R, Dougados M, Hermann KG, Landewe R, Maksymowych W, et al. The Assessment of SpondyloArthritis international Society (ASAS) handbook: a guide to assess spondyloarthritis. Ann Rheum Dis. 2009;68(Suppl 2):ii1–44.
Machado PM, Landewe R, Heijde DV, Assessment of SpondyloArthritis international S. Ankylosing Spondylitis Disease Activity Score (ASDAS): 2018 update of the nomenclature for disease activity states. Ann Rheum Dis. 2018;77(10):1539–40.
Creemers MC, Franssen MJ, van't Hof MA, Gribnau FW, van de Putte LB, van Riel PL. Assessment of outcome in ankylosing spondylitis: an extended radiographic scoring system. Ann Rheum Dis. 2005;64(1):127–9.
MacKay K, Mack C, Brophy S, Calin A. The Bath Ankylosing Spondylitis Radiology Index (BASRI): a new, validated approach to disease assessment. Arthritis Rheum. 1998;41(12):2263–70.
Dagfinrud H, Mengshoel AM, Hagen KB, Loge JH, Kvien TK. Health status of patients with ankylosing spondylitis: a comparison with the general population. Ann Rheum Dis. 2004;63(12):1605–10.
Singh JA, Strand V. Spondyloarthritis is associated with poor function and physical health-related quality of life. J Rheumatol. 2009;36(5):1012–20.
Davis JC, van der Heijde D, Dougados M, Woolley JM. Reductions in health-related quality of life in patients with ankylosing spondylitis and improvements with etanercept therapy. Arthritis Rheum. 2005;53(4):494–501.
Klingberg E, Lorentzon M, Mellstrom D, Geijer M, Gothlin J, Hilme E, Hedberg M, Carlsten H, Forsblad-d'Elia H. Osteoporosis in ankylosing spondylitis - prevalence, risk factors and methods of assessment. Arthritis Res Ther. 2012;14(3):R108.
Ward MM. Health-related quality of life in ankylosing spondylitis: a survey of 175 patients. Arthritis Care Res. 1999;12(4):247–55.
Webers C, Essers I, Ramiro S, Stolwijk C, Landewe R, van der Heijde D, van den Bosch F, Dougados M, van Tubergen A. Gender-attributable differences in outcome of ankylosing spondylitis: long-term results from the Outcome in Ankylosing Spondylitis International Study. Rheumatology (Oxford). 2016;55(3):419–28.
Loge JH, Kaasa S. Short form 36 (SF-36) health survey: normative data from the general Norwegian population. Scand J Soc Med. 1998;26(4):250–8.
Bodur H, Ataman S, Rezvani A, Bugdayci DS, Cevik R, Birtane M, Akinci A, Altay Z, Gunaydin R, Yener M, et al. Quality of life and related variables in patients with ankylosing spondylitis. Qual Life Res. 2011;20(4):543–9.
Ibn Yacoub Y, Amine B, Laatiris A, Abouqal R, Hajjaj-Hassouni N. Health-related quality of life in Moroccan patients with ankylosing spondylitis. Clin Rheumatol. 2011;30(5):673–7.
Fernandez-Carballido C, Navarro-Compan V, Castillo-Gallego C, Castro-Villegas MC, Collantes-Estevez E, de Miguel E, Esperanza Study G. Disease activity as a major determinant of quality of life and physical function in patients with early axial spondyloarthritis. Arthritis Care Res (Hoboken). 2017;69(1):150–5.
Cho H, Kim T, Kim TH, Lee S, Lee KH. Spinal mobility, vertebral squaring, pulmonary function, pain, fatigue, and quality of life in patients with ankylosing spondylitis. Ann Rehabil Med. 2013;37(5):675–82.
Lopez-Medina C, Garrido-Castro JL, Castro-Jimenez J, Gonzalez-Navas C, Calvo-Gutierrez J, Castro-Villegas MC, Ortega-Castro R, Escudero-Contreras A, Font-Ugalde P, Collantes-Estevez E. Evaluation of quality of life in patients with axial spondyloarthritis and its association with disease activity, functionality, mobility, and structural damage. Clin Rheumatol. 2018;37(6):1581–8.
Essers I, Ramiro S, Stolwijk C, Blaauw M, Landewe R, van der Heijde D, van den Bosch F, Dougados M, van Tubergen A. Do extra-articular manifestations influence outcome in ankylosing spondylitis? 12-year results from OASIS. Clin Exp Rheumatol. 2016;34(2):214–21.
Bussing A, Ostermann T, Neugebauer EA, Heusser P. Adaptive co** strategies in patients with chronic pain conditions and their interpretation of disease. BMC Public Health. 2010;10:507.
Fernandez O, Baumstarck-Barrau K, Simeoni MC, Auquier P, MusiQo Lsg. Patient characteristics and determinants of quality of life in an international population with multiple sclerosis: assessment using the MusiQoL and SF-36 questionnaires. Mult Scler. 2011;17(10):1238–49.
Parker PA, Baile WF, de Moor C, Cohen L. Psychosocial and demographic predictors of quality of life in a large sample of cancer patients. Psycho-Oncology. 2003;12(2):183–93.
Sarna L, Padilla G, Holmes C, Tashkin D, Brecht ML, Evangelista L. Quality of life of long-term survivors of non-small-cell lung cancer. J Clin Oncol. 2002;20(13):2920–9.
Schunk M, Reitmeir P, Ruckert-Eheberg IM, Tamayo T, Schipf S, Meisinger C, Peters A, Scheidt-Nave C, Ellert U, Hartwig S, et al. Longitudinal change in health-related quality of life in people with prevalent and incident type 2 diabetes compared to diabetes-free controls. PLoS One. 2017;12(5):e0176895.
Rao Y, Xu X, Liu D, Reis C, Newman IM, Qin L, Sharma M, Shen J, Zhao Y. Health-related quality of life in patients with arthritis: a cross-sectional survey among middle-aged adults in Chongqing, China. Int J Environ Res Public Health. 2018;15(4):768.
Wang R, Wu C, Zhao Y, Yan X, Ma X, Wu M, Liu W, Gu Z, Zhao J, He J. Health related quality of life measured by SF-36: a population-based study in Shanghai, China. BMC Public Health. 2008;8:292.
Michael YL, Berkman LF, Colditz GA, Kawachi I. Living arrangements, social integration, and change in functional health status. Am J Epidemiol. 2001;153(2):123–31.
Fossa SD, Hess SL, Dahl AA, Hjermstad MJ, Veenstra M. Stability of health-related quality of life in the Norwegian general population and impact of chronic morbidity in individuals with and without a cancer diagnosis. Acta Oncol. 2007;46(4):452–61.
Morck B, Pullerits R, Geijer M, Bremell T, Forsblad-d'Elia H. Infliximab dose reduction sustains the clinical treatment effect in active HLAB27 positive ankylosing spondylitis: a two-year pilot study. Mediat Inflamm. 2013;2013:289845.
Revicki DA, Luo MP, Wordsworth P, Wong RL, Chen N, Davis JC Jr, Group AS. Adalimumab reduces pain, fatigue, and stiffness in patients with ankylosing spondylitis: results from the adalimumab trial evaluating long-term safety and efficacy for ankylosing spondylitis (ATLAS). J Rheumatol. 2008;35(7):1346–53.
Deodhar AA, Dougados M, Baeten DL, Cheng-Chung Wei J, Geusens P, Readie A, Richards HB, Martin R, Porter B. Effect of secukinumab on patient-reported outcomes in patients with active ankylosing spondylitis: a phase III randomized trial (MEASURE 1). Arthritis Rheumatol. 2016;68(12):2901–10.
Acknowledgements
We wish to thank all the patients who participated in the study.
Funding
This study was supported by grants from the Health and Medical Care Executive Board of the Västra Götaland, Göteborg’s Association Against Rheumatism, Västerbotten’s Association Against Rheumatism, The Swedish Research Council, The Swedish Association Against Rheumatism, The Swedish Society of Medicine, The Göteborg Medical Society, the Region Västra Götaland and the County of Västerbotten (agreement concerning research and education of doctors).
Availability of data and materials
The data sets analysed during the current study are not publicly available due to the Swedish legislation (the Personal Data Act), but a limited and fully anonymised data set that supports the main analyses is available from the corresponding author on request.
Author information
Authors and Affiliations
Contributions
LL and JBR participated in analysis and interpretation of data and drafting the manuscript, AD and EK participated in the design of the study and acquisition, analysis and interpretation of data. LTHJ participated in drafting the manuscript and interpretation of data. HFd’E participated in the conception and design of the work, acquisition, analysis and interpretation of data and drafting the manuscript. All authors critically reviewed the manuscript and approved the final version to be published.
Corresponding author
Ethics declarations
Ethics approval and consent to participate
The study was approved by the regional ethics committee in Gothenburg, Sweden (reference number Dnr 597-08) and was performed in accordance with the Helsinki declaration. All participants gave their written informed consent.
Consent for publication
Not applicable.
Competing interests
LTHJ has received Advisory Board Fees from Novartis, Celgene and MSD, outside the submitted work. HFd’E has received Advisory Board Fees from Sandoz, Novartis and Abbvie outside the submitted work and an unrestricted grant from Novartis. LL, JRB, AD and EK report no competing interests.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Additional files
Additional file 1:
Table S1. Results of the SF-36 in patients with ankylosing spondylitis and in controls from the general population. Table S2. Comparisons of variables in patients with ankylosing spondylitis with scores below or above the median PCS score. Table S3. Comparisons of variables in patients with ankylosing and spondylitis scores below or above the median MCS score. Table S4. Univariate logistic regression analyses with PCS score below the median values as dependent variable and all assessed variables as covariates. Table S5. Univariate logistic regression analyses with MCS score below the median values as dependent variable and all assessed variables as covariates. Table S6. Multivariable logistic regression analyses with PCS and MCS scores below their median values as dependent variables and demographics as covariates. (DOCX 92 kb)
Rights and permissions
Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
About this article
Cite this article
Law, L., Beckman Rehnman, J., Deminger, A. et al. Factors related to health-related quality of life in ankylosing spondylitis, overall and stratified by sex. Arthritis Res Ther 20, 284 (2018). https://doi.org/10.1186/s13075-018-1784-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1186/s13075-018-1784-8